当前位置: X-MOL 学术bioRxiv. Bioinform. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
RBCeq: An Integrated Bioinformatics Algorithm Designed to Improve Blood Type Compatibility Testing
bioRxiv - Bioinformatics Pub Date : 2021-01-20 , DOI: 10.1101/2021.01.13.426510
Sudhir Jadhao , Candice Davison , Eileen V. Roulis , Elizna M. Schoeman , Mayur Divate , Arvind Jaya Shankar , Simon Lee , Natalie M. Pecheniuk , David O Irving , Catherine A. Hyland , Robert L. Flower , Shivashankar H. Nagaraj

While blood transfusion is an essential cornerstone of hematological care, patients that require repetitive transfusion remain at persistent risk of alloimmunization due to the diversity of human blood group polymorphisms. Next-generation sequencing (NGS) is an effective means of identifying genotypic and phenotypic variations among the blood groups, while the accurate interpretation of such NGS data is currently hampered by a lack of accessibility to bioinformatics support. To address this unmet need, we have developed the RBCeq (https://www.rbceq.org/) platform, which consists of a novel bioinformatics algorithm coupled with a user-friendly web server capable of comprehensively delineating different blood group variants from genomics data with advanced visualization of results. The software profiles genomic data for 36 blood group systems, including two transcription factors and can identify small genetic alterations, including small indels and copy number variants. The RBCeq algorithm was validated on 403 samples which include 58 complex serology cases from Australian Red Cross LifeBlood, 100 samples from The MedSeq Project (phs000958) and a further 245 from Indigenous Australian participants. The final blood typing data from RBCeq was 99.83% concordant for 403 samples (85 different antigens in 21 blood group systems) with that listed from the International Society for Blood Transfusion database.

中文翻译:

RBCeq:一种旨在改善血型兼容性测试的集成生物信息学算法

尽管输血是血液学治疗的重要基础,但由于人类血型多态性的多样性,需要重复输血的患者仍然面临同种免疫的持续风险。下一代测序(NGS)是识别血型之间基因型和表型变异的有效手段,而由于缺乏生物信息学支持,目前阻碍了此类NGS数据的准确解释。为了满足这一未满足的需求,我们开发了RBCeq(https://www.rbceq.org/)平台,该平台由新颖的生物信息学算法与用户友好的Web服务器组成,该服务器能够全面描述基因组学中的不同血型变异数据具有高级可视化结果。该软件可以分析36个血型系统的基因组数据,包括两个转录因子,可以识别小的遗传变异,包括小的indel和拷贝数变异。RBCeq算法在403个样本中得到了验证,其中包括来自澳大利亚红十字会血液系统的58个复杂血清学病例,来自MedSeq项目(phs000958)的100个样本以及来自澳大利亚土著居民的245个样本。来自RBCeq的最终血型数据与403个样本(21个血型系统中的85种不同抗原)的99.83%一致,与国际输血协会数据库中列出的数据一致。MedSeq项目(phs000958)的100个样本,澳大利亚土著居民的245个样本。来自RBCeq的最终血型数据与403个样本(21个血型系统中的85种不同抗原)的99.83%一致,与国际输血协会数据库中列出的数据一致。MedSeq项目(phs000958)的100个样本,澳大利亚土著居民的245个样本。来自RBCeq的最终血型数据与403个样本(21个血型系统中的85种不同抗原)的99.83%一致,与国际输血协会数据库中列出的数据一致。
更新日期:2021-01-21
down
wechat
bug